paid / Tucson, AZ / full-time
The Data Science Institute and the University of Arizona College of Agriculture and Life Sciences Data Science team have two openings for a scientific software engineer and educator. The ideal candidate is either a domain scientist with software and programming experience or a software engineer with experience applying computational and statistical methods to support scientific research.
The incumbents will split time between providing support on research projects and offering training across campus. With multiple openings, we are hoping to find two with complimentary experience and skills.
The education component of the position will develop, enhance and expand the Data Science Institute’s capabilities to develop curriculum and provide just-in-time training, workshops, consultation and support for students, faculty and staff wanting to learn foundational tools and concepts of data science and reproducible computational science. This will include broad collaboration across the data science community, including with other campus partners and trainers related to computational science and data science.
The research component of the position will directly support research projects across the College of Agriculture and Life Sciences, Cooperative Extension, and Experiment Station. They will be expected to conduct and communicate reproducible research, data management, and analysis.
The positions will be split approximately 50:50 between research and education.
Building computational and data science capacity:
- Develop and deliver workshops and related training materials on computational science and data science. Workshop topics may include but are not limited to computational notebooks, tools for reproducible computing, statistics, remote sensing, machine learning, visualization, and data management.
- Work with campus partners and other trainers in delivery of workshops and training materials related to data science.
- Participate with and offer trainings for programs such as the Data Science Ambassadors, Roots for Resilience Graduate Fellowship and the Data Science Fellows programs.
- Use and follow best practices in developing training materials, scientific computing, data and code management, documentation and digital forms of communication.
Enable research in the College of Agriculture and Life Sciences, Cooperative Extension, and Experiment Station.
Develop and lead 'incubator' projects with researchers across campus.
Provide computational, statistical, and domain expertise for larger, externally funded projects. Possible scientific domain knowledge include: earth and environmental sciences, agriculture, or ecophysiology.
The incumbent will have flexibility to work on a variety of other projects across the College of Agriculture and Life Sciences, Experiment Station, and Cooperative Extension. You can learn more about our group at datascience.cals.arizona.edu.
- Engage and interact with campus collaborators and related professional organizations; represent the Data Science Institute at workshops, meetings and conferences.
- Contribute to University of Arizona data science community events such as Coffee & Code, Hacky Hour, Women in Data Science, RezBaz, and Machine Learning Literacy Project events.
- Develop analytical pipelines
- Work with researchers to enable new computational methods
- Meet regularly with group members and collaborators
- Work in an iterative, agile environment
Examples of Project Responsibilities:
- Run ecological models using the PEcAn framework
- Develop reproducible analyses and scalable workflows
- Develop and apply statistical models
- Develop, refactor, test, and document scientific R packages, Python libraries
- Create and improve visualizations and interpretation of results
- Curate and manage data
- Develop APIs, Dashboards, and other custom software
- Master’s degree required.
- Experience in scientific software development.
- Proficiency in R or Python.
- Experience with version control
- Experience with cloud and / or cluster computing.
- Experience teaching computational skills.
- Demonstrated ability to work collaboratively in a team.
- PhD in a related field. Experience with Bayesian analysis, data management, scientific publishing, project management, containers, testing, remote sensing, R package, or Python library development.
- Possible scientific domain knowledge include: earth and environmental sciences, agriculture, or ecophysiology.
$55,000 - $70,000
To read the full job description and apply: Scientific Programmer and Educator